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Conditionally heteroscedastic unobserved component models and their reduced form

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  • Pellegrini, Santiago
  • Ruiz, Esther
  • Espasa, Antoni

Abstract

The reduced form of the local level model with conditionally heteroscedastic GARCH(1,1) noises is analyzed. We show that the IMA-GARCH model is a good alternative but its conditional heteroscedasticity is weaker than this of the unobserved disturbances.

Suggested Citation

  • Pellegrini, Santiago & Ruiz, Esther & Espasa, Antoni, 2010. "Conditionally heteroscedastic unobserved component models and their reduced form," Economics Letters, Elsevier, vol. 107(2), pages 88-90, May.
    • Handle: RePEc:eee:ecolet:v:107:y:2010:i:2:p:88-90
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    References listed on IDEAS

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    1. Paolo Zaffaroni, 2007. "Contemporaneous aggregation of GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(4), pages 521-544, July.
    2. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    3. Maravall, Agustin, 1983. "An Application of Nonlinear Time Series Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(1), pages 66-74, January.
    4. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    5. Broto, Carmen & Ruiz, Esther, 2006. "Unobserved component models with asymmetric conditional variances," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2146-2166, May.
    6. Pellegrini, Santiago & Ruiz Ortega, Esther & Espasa, Antoni, 2007. "The relationship between ARIMA-GARCH and unobserved component models with GARCH disturbances," DES - Working Papers. Statistics and Econometrics. WS ws072706, Universidad Carlos III de Madrid. Departamento de Estadística.
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    Cited by:

    1. Bonga-Bonga, Lumengo & Montshioa, Keitumetse, 2024. "Navigating extreme market fluctuations: asset allocation strategies in developed vs. emerging economies," MPRA Paper 119910, University Library of Munich, Germany.
    2. Pellegrini, Santiago & Ruiz, Esther & Espasa, Antoni, 2011. "Prediction intervals in conditionally heteroscedastic time series with stochastic components," International Journal of Forecasting, Elsevier, vol. 27(2), pages 308-319.
    3. Montshioa, Keitumetse & Muteba Mwamba, John Weirstrass & Bonga-Bonga, Lumengo, 2021. "Asset allocation in extreme market conditions: a comparative analysis between developed and emerging economies," MPRA Paper 106248, University Library of Munich, Germany.

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